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Title: Small-sample solution to the two-sample problem for quantiles using melded random confidence intervals

Source: FS Research Paper

Author(s)Arvanitis, Matthew

Publication Year: 2022  View PDF »

Category: Research Papers

Abstract: A new nonparametric solution to the two-sample problem for quantiles is proposed. This solution is applicable to small samples and/or extreme quantiles, and it prioritizes limiting Type I error to the indicated level of significance over optimizing power or confidence interval width. Aside from continuity, no assumptions about the distributions are made. In this approach, nonparametric random confidence intervals obtained from the samples are “melded,” resulting in a nonparametric confidence interval for the difference between the two population quantiles with a specified confidence level. Simulations and an application to lumber strength characteristics are exhibited.

Keywords: nonparametric; quantile; two-sample problem; small sample; melded confidence interval; exact random nonparametric confidence interval; lumber quantile comparison

Publication Review Process: Informally Refereed (Peer-Reviewed)

File size: 641 kb(s)

Date posted: 04/01/2022

This publication is also viewable on Treesearch:  view
RITS Product ID: 10456
Current FPL Scientist associated with this product
Arvanitis, Matthew
Mathematical Statistician

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